Small Size Team

Accelerators

People Overview Downloads Multi-Media Team Pages Publications
People Current: Stefan Zickler, Joydeep Biswas, Manuela Veloso Past: Gabriel Levi, Philip Wasserman, James Bruce, Mike Licitra, Michael Bowling, Brett Browning, Michael Sokolsky, Dinesh Govindaraju, Jennifer Lin, Betsy Ricker, David Rozner, Paul Harada, Peter Stone, Kwun Han, Sorin Achim.

Overview

Small-size robot soccer is a game between two autonomous teams of 5 robots with an orange golf ball. The robots compete in a game of soccer with rules dictated by a human referee. Referee signals are transmitted to each team computer via the referee box. Small-size differs from the other leagues in a number of ways. The robots, which are built by the teams, must fit within a 180cm cylinder that is 15cm tall. The robots must also be relatively concave and have no holes that swallow the ball by more than 20% of its surface area when projected onto the ground (ie. about 1cm of depth). Overhead cameras are allowed in addition to on-robot sensing. Additionally, off-field computers are allowed to 'simplify' the distributed computation challenges. These rules allow teams to focus more on the behavior and teamwork part of the robot soccer problem rather than on single robot issues such as localization, which are an ever present problem in leagues such as the Sony AIBO league. As such, small-size league games are amongst the fastest and most dynamic within the leagues that make up RoboCup. Watch some of our team videos (see below) and see for yourself.

Carnegie Mellon has participated in the small-size league since its inception in 1997. We have won the competition twice, have been semi-finalists, and quarter finalists twice. Our team has a number of unique features, including:

• A unique hierarchical control system designed for its control response properties rather than adherence to a particular deliberation vs. reactive philosophy
• An adaptive strategy engine that adapts team behavior based on its performance as the game progresses.
• A play based representation for human readable representation of team behavior under different situations.
• A tactics layer for encoding of individual robot skills. This includes a two layered finite-state-machine for controlling actions, facilities for rapidly evaluating different objective functions, obstacle free near-optimal navigation, and near-optimal trapezoidal motion control.
• Very fast randomized path planning (~2ms per plan) for efficient robot navigation
• A very fast color vision library CMVision, which is also used on our CMPack, Sony AIBO team
• A robust high-level vision system that includes fast calibration programs for camera geometry calibration, and color threshold calibrations.
• A realistic 3D simulator that incorporates a realistic physics engine with reconfigurable robot parameters.

Downloads

We have a number of Open Source releases, of both software and hardware, that are available to everyone. These items are available under the GNU LGPL license. We just ask that if you use our releases that you cite our relevant papers appropriately (see our publication list).